Abstract Sarcoidosis is an inflammatory disease of unknown etiology that occurs worldwide and is characterized by granuloma formation in different organs. No specific test has been developed to diagnose this disease. Confirmation of non-caseating granuloma in tissue biopsy of involved organs in the absence of other causes is the current state of the art for diagnosing sarcoidosis. We propose to test the hypothesis that overall immunity plays a prominent role in the pathogenesis of sarcoidosis, since abnormalities of the immune function and the presence of various antibodies/autoantibodies occurs in this disorder. Using a high throughput method, we have developed a complex epitope library derived from materials of sarcoidosis patients. The epitopes are derived from a T7 phage cDNA library of potential sarcoidosis antigens using mRNA isolated from bronchoalveolar (BAL) cells and white blood cells (WBCs) of patients with sarcoidosis. This cDNA library containing large numbers of epitopes has been immunoscreened with sera from patients with sarcoidosis containing high titer IgG antibodies and the cloned phages have been used to construct an antigen microarray to detect antibodies against sarcoid antigen(s) in the sera of test subjects. We have identified a panel of biomarkers/classifiers with high sensitivity and specificity that can discriminate between sera of patients with sarcoidosis and healthy controls. In our study we used 80-90% of African American female population of sarcoidosis patients and these patients were not strictly age-matched with healthy controls. To test this hypothesis, we propose to use banked plasma from diversified population of sarcoidosis patients and aged-matched healthy controls, enrolled in the NIH-sponsored A Case Controlled Etiology of Sarcoidosis Study (ACCESS). We would like to use these plasma samples and the clinical data from ACCESS biorepository to first test and validate the bioreactivity of plasma obtained independently from cases and controls (ACCESS) to obtain a panel of diagnostic biomarkers/classifiers, which can discriminate between sarcoidosis and healthy controls. Second, we will determine whether the discovered biomarkers/classifiers can predict the clinical outcome and Scadding stages of sarcoidosis. In future, this approach could be used to identify a panel of biomarkers useful for diagnosis of various organ involvements in sarcoidosis and differential diagnosis of various granulomatous diseases or response to treatment in sarcoidosis subjects.